Citywide Metro-to-Bus Transfer Behavior Identification Based on Combined Data from Smart Cards and GPS

The aim of this study is to develop a fast data fusion method for recognizing metro-to-bus transfer trips based on combined data from smart cards and a GPS system. The method is intended to establish station- and time-specific elapsed time thresholds for overcoming the limitations of one-size-fits-all criterion which is not sufficiently convincing for different transfer pairs and personal characteristics. Firstly, a data fusion method with bus smart card data and GPS data is proposed to supplement absent bus boarding information in the smart card data. Then, a model for identifying metro-to-bus interchange trips is derived based on two rules about maximal allowable transfer distance and elapsed transfer time threshold. Finally, in tests that used half-monthly field smart card data and GPS data from Shenzhen, China, the results recognized by the proposed method were more consistent with the actual surveyed group transfer time with a P value of 0.17 determined by Mann–Whitney U test. The comparison analysis showed that the proposed method can be widely applied to successfully identify and interpret metro-to-bus interchange behavior beyond a static transfer time threshold of 30 min.

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An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis

Journal of Advanced Transportation ◽

10.1155/2018/4047682 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

De Zhao ◽

Wei Wang ◽

Ghim Ping Ong ◽

Yanjie Ji

Keyword(s):

Association Rules ◽

Smart Card ◽

Primary Objective ◽

Smart Cards ◽

The Public ◽

Trip Chain ◽

Chain Analysis ◽

Smart Card Data ◽

Transfer Behavior ◽

Novel Method

Smart card data provide valuable insights and massive samples for enhancing the understanding of transfer behavior between metro and public bicycle. However, smart cards for metro and public bicycle are often issued and managed by independent companies and this results in the same commuter having different identity tags in the metro and public bicycle smart card systems. The primary objective of this study is to develop a data fusion methodology for matching metro and public bicycle smart cards for the same commuter using historical smart card data. A novel method with association rules to match the data derived from the two systems is proposed and validation was performed. The results showed that our proposed method successfully matched 573 pairs of smart cards with an accuracy of 100%. We also validated the association rules method through visualization of individual metro and public bicycle trips. Based on the matched cards, interesting findings of metro-bicycle transfer have been derived, including the spatial pattern of the public bicycle as first/last mile solution as well as the duration of a metro trip chain.

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Community Bus Demand Characteristics Analysis Based on Smart Card Data and GPS Data

ICTE 2015 ◽

10.1061/9780784479384.194 ◽

2015 ◽

Author(s):

Pengyao Ye ◽

Shengchao Yang ◽

Ling Xu

Keyword(s):

Smart Card ◽

Gps Data ◽

Demand Characteristics ◽

Smart Card Data ◽

Characteristics Analysis

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Behavioural data mining of transit smart card data: A data fusion approach

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2014.05.012 ◽

2014 ◽

Vol 46 ◽

pp. 179-191 ◽

Cited By ~ 128

Author(s):

Takahiko Kusakabe ◽

Yasuo Asakura

Keyword(s):

Data Mining ◽

Data Fusion ◽

Smart Card ◽

Smart Card Data ◽

Transit Smart Card ◽

Fusion Approach

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Spatial-Temporal Travel Behavior Analysis of Transit Passengers Based on Massive Smart Card Data and GPS Data

CICTP 2020 ◽

10.1061/9780784482933.285 ◽

2020 ◽

Author(s):

Yuqian Li ◽

Xiaoyu He

Keyword(s):

Behavior Analysis ◽

Smart Card ◽

Travel Behavior ◽

Gps Data ◽

Smart Card Data

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Robot Navigation Using a DR/GPS Data Fusion

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.392.261 ◽

2013 ◽

Vol 392 ◽

pp. 261-266 ◽

Cited By ~ 4

Author(s):

Yuan Liang Zhang ◽

Jong Ho Park ◽

Nam O Sel ◽

Kil To Chong

Keyword(s):

Data Fusion ◽

Mobile Robot ◽

Navigation System ◽

Robot Navigation ◽

Mobile Robot Navigation ◽

Gps Data ◽

Fusion Method ◽

Gps Receiver ◽

Differential Gps ◽

Navigation Information

Dead Reckoning (DR) is one of the frequently used navigation system for a mobile robot. It provides short term navigation information but its error can accumulate over time without limit. The Global Positioning System (GPS) can be used for localization and navigation outdoors wherein the removal of the SA Policy improved the accuracy of the GPS for civilian use but the error is still quite large. Standard Differential GPS (DGPS) can be used to achieve an error of less than one meter but the costs are prohibitive in terms of commercializing it into the mass market. In this research study, a cheap GPS receiver was used for the navigation system of a mobile robot outdoors in which a new Kalman-filter based DR/GPS data fusion method was utilized. This proposed method is based on the characteristics of the GPS receiver. Fusing the data from the GPS receiver and the DR system provided precise navigation information for the mobile robot. Simulation was performed to check and validate the effectiveness of the proposed fusion method and good results showed its potential for mobile robot navigation outdoors.

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